Optimization model to assess electric vehicles as an alternative for fleet composition in station-based car sharing systems
Optimization model to assess electric vehicles as an alternative for fleet composition in station-based car sharing systems
Electromobility can be one of many solutions to the environmental challenge facing society nowadays, and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimization model to evaluate the influence of the selected parameters in the economic and environmental dimensions of different vehicle technologies and the optimal fleet composition for small-scale car sharing. The model is applied to car sharing system VAMO, located in Fortaleza (Brazil), and the decision variables comprise pure electric (BEV), plug-in hybrid (PHEV) and internal combustion engine (ICEV) vehicles. Baseline results are strongly influenced by the economic dimension, showing that existing infrastructure and well-established technology are great advantages for ICEVs and major barriers for EVs. In that sense, ethanol arises as a balanced alternative between costs and emissions. However, EVs represent a strong environmental appeal considering global emissions and local pollutants and even with economic losses in the short-term, investments in electromobility could come out as a positioning strategy in a future business with strong perspectives of growth, be it technological or in market share. The results suggest that all vehicle technologies will play an important role during this transition period to a desired sustainable mobility.
Car sharing, Electric vehicle, Optimization, Sustainable mobility
173-196
Lemme, Rafael F.F.
f49b878e-490c-4f8c-af92-f09f3146030f
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Bahiense, Laura
48a5c2a4-d43b-4445-983f-e0637753074e
February 2019
Lemme, Rafael F.F.
f49b878e-490c-4f8c-af92-f09f3146030f
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Bahiense, Laura
48a5c2a4-d43b-4445-983f-e0637753074e
Lemme, Rafael F.F., Arruda, Edilson F. and Bahiense, Laura
(2019)
Optimization model to assess electric vehicles as an alternative for fleet composition in station-based car sharing systems.
Transportation Research Part D: Transport and Environment, 67, .
(doi:10.1016/j.trd.2018.11.008).
Abstract
Electromobility can be one of many solutions to the environmental challenge facing society nowadays, and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimization model to evaluate the influence of the selected parameters in the economic and environmental dimensions of different vehicle technologies and the optimal fleet composition for small-scale car sharing. The model is applied to car sharing system VAMO, located in Fortaleza (Brazil), and the decision variables comprise pure electric (BEV), plug-in hybrid (PHEV) and internal combustion engine (ICEV) vehicles. Baseline results are strongly influenced by the economic dimension, showing that existing infrastructure and well-established technology are great advantages for ICEVs and major barriers for EVs. In that sense, ethanol arises as a balanced alternative between costs and emissions. However, EVs represent a strong environmental appeal considering global emissions and local pollutants and even with economic losses in the short-term, investments in electromobility could come out as a positioning strategy in a future business with strong perspectives of growth, be it technological or in market share. The results suggest that all vehicle technologies will play an important role during this transition period to a desired sustainable mobility.
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e-pub ahead of print date: 6 December 2018
Published date: February 2019
Keywords:
Car sharing, Electric vehicle, Optimization, Sustainable mobility
Identifiers
Local EPrints ID: 447653
URI: http://eprints.soton.ac.uk/id/eprint/447653
ISSN: 1361-9209
PURE UUID: 3e4f2765-dab8-46de-b2be-78935365db0d
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Date deposited: 17 Mar 2021 17:39
Last modified: 18 Mar 2024 03:59
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Contributors
Author:
Rafael F.F. Lemme
Author:
Edilson F. Arruda
Author:
Laura Bahiense
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